Compare Delta Lake vs. Scalytics Connect

Delta Lake serves as an open-source storage layer that integrates ACID transactions into Apache Spark™ and big data operations. In typical data lakes, multiple pipelines operate simultaneously to read and write data, which often forces data engineers to engage in a complex and time-consuming effort to maintain data integrity because transactional capabilities are absent. By incorporating ACID transactions, Delta Lake enhances data lakes and ensures a high level of consistency with its serializability feature, the most robust isolation level available. For further insights, refer to Diving into Delta Lake: Unpacking the Transaction Log. In the realm of big data, even metadata can reach substantial sizes, and Delta Lake manages metadata with the same significance as the actual data, utilizing Spark's distributed processing strengths for efficient handling. Consequently, Delta Lake is capable of managing massive tables that can scale to petabytes, containing billions of partitions and files without difficulty. Additionally, Delta Lake offers data snapshots, which allow developers to retrieve and revert to previous data versions, facilitating audits, rollbacks, or the replication of experiments while ensuring data reliability and consistency across the board.

Scalytics Connect combines data mesh and in-situ data processing with polystore technology, resulting in increased data scalability, increased data processing speed, and multiplying data analytics capabilities without losing privacy or security. You take advantage of all your data without wasting time with data copy or movement, enable innovation with enhanced data analytics, generative AI and federated learning (FL) developments. Scalytics Connect enables any organization to directly apply data analytics, train machine learning (ML) or generative AI (LLM) models on their installed data architecture.